QRM Conference 2024

Places are limited and priority will be given to those who have participated in QRM courses or have registered to become member of the QRM network.

Register no later than May 28 via the registration form. Conference dinner registration is only available to those who sign up by May 14.

The conference dinner, free of charge, takes place at OGBG Bar & Restaurang. Vegetarian buffet will be served to those who wish to join and indicate it when registering.

Title

Intraindividual Structural Equation Models

Keynote abstract 

There is an increasing interest in intraindivudal (cf. micro-longitudinal, within-person, ideographic) educational research using intensive longitudinal data, such that multiple repeated measures are collected within a defined time-window (e.g., five times a day for two weeks). The broad term “intraindividual” structural equation models (ISEM) includes multilevel SEM (MSEM), dynamic SEM (DSEM) and others (e.g., growth models, vector autoregressive models, multilevel models for change), all using time-points nested in persons as the basic design. Intensive longitudinal datasets can include self-reports or multiple-reporter data (e.g., diaries, experience sampling, ecological momentary assessment, observations of behaviour), task-data (e.g., trace-data, accuracy and response-times), real-time ambulatory data (e.g., from wearable monitors for physical activity or electrodermal activity, or stationary devices for eye-tracking or joy-stick coded observations), or mixtures of these. Researchers face at least three challenges in designing intraindividual studies, including (1) designing an optimal multilevel data-structure, (2) combining multiple sources and formats of data, and (3) specifying appropriate statistical models. Time-series-based Dynamic Structural Equation Models (DSEM) are emerging, adding to the tool-box of existing techniques. Using DSEM we can focus on intraindividual processes, rather than developmental progression or contextual effects. 

In the talk, Lars-Erik will illustrate intensive longitudinal designs and ISEMs from educational research, in order to highlight their relevance for understanding processes of learning and teaching. Overall, findings from process-studies can promote the conceptualization of individualized teaching or personalized interventions. He will end on a summary of the opportunities and challenges facing researchers in this emerging field, going forward.

Keynote speaker short bio

Lars-Erik Malmberg is Professor of Quantitative Methods in Education, at the Department of Education, University of Oxford, UK. He has 100+ publications. He was Editor-in-Chief of the Journal of Learning and Instruction 2018-21. His current research interests are on intraindividual approaches to learning processes, and modelling of intensive longitudinal data. He has published on effects of education, child care and parenting on developmental and educational outcomes, and teacher development. He applies advanced quantitative models, including multilevel and dynamic structural equation models to the investigation of substantive research questions in education. Links between education phenomena and physiology were explored in the Emerging Field Group “The potential of biophysiology for understanding learning and teaching experiences”.

Read more about Lars-Erik Malmberg, University of Oxford

Presentation slides for the keynote can be found here

Title

Bringing it all together—How International Large-Scale Assessment data can inform meta-analyses in education

Keynote abstract 

Meta-analyses are key sources of information for educational researchers. They bring together evidence on, for instance, the relations among constructs, the effects of interventions, or differences in constructs between educationally relevant groups. While meta-analyses have a long tradition, they still face several issues, such as small-sample studies resulting in the lack of statistical power or study measures that lack reliability and validity evidence. International large-scale assessments (ILSAs) in education could help to resolve some of these issues. 

In this keynote, Ronny Scherer will describe, discuss, and illustrate ways in which ILSA data can be integrated into meta-analyses in education and which benefits an integration has. He will also highlight key challenges associated with extracting effect sizes from ILSAs and addressing the oftentimes complex nature of the meta-analytic data.

Keynote speaker short bio

Ronny Scherer is a full professor of educational assessment and measurement. He is a member of the Centre for Educational Measurement (CEMO) and the co-director of the Centre for Research on Equality in Education (CREATE) at the University of Oslo. His research focuses on the methods and substantive issues related to research syntheses, the analysis of international large-scale assessments in education, and educational equality.

Read more about Ronny Scherer, University of Oslo

Presentation slides for the keynote can be found here

Workshop A

Title: Getting started with R + and getting help from AI

R is an excellent tool for quantitative data analysis and is free of charge for students and researchers alike, ensuring broad accessibility to all. However, starting to use R for statistical analysis can be challenging, particularly because the threshold of mastering R's programming language poses a significant learning curve for effectively writing and understanding the code. A simple and easy-to-use solution to overcoming this threshold is generative AI, such as ChatGPT, Copilot, or Gemini. AI offers an accessible gateway to getting acquainted with R, serving as a supportive partner in analyzing data by simplifying the process of learning and applying R's programming concepts. In this workshop, you will work with AI to learn R from the ground up, including writing code, fixing broken code, and explaining how the R programming language works.

No knowledge of AI or R is required for this workshop but you should be familiar with basic statistical analyses such as comparing means, comparing frequencies, correlation, and regression. 

Workshop leaders

Håkan Forsberg , Uppsala University, hakan.forsberg@edu.uu.se
Håkan Forsberg is a researcher and associate professor in the Sociology of Education at Uppsala University. His primary research focuses on the configurations of school markets, as well as the segregation of schools and housing, particularly in relation to families' educational strategies. His research primarily utilizes analyses of full population register data.

Erika Majoros, Umeå University, erika.majoros@umu.se
Erika works as a postdoctoral research fellow at Umeå University. Her main research interests are in the areas of large-scale educational assessments, psychometrics, comparative education, educational policy, and assessment accommodations.

Jonathan Wedman, TUV, Umeå University, jonathan.wedman@umu.se
Jonathan is a researcher and associate professor in educational measurement and a distinguished university teacher at Umeå university. His main research interests are in the areas of large-scale educational assessments, psychometrics, and classroom assessment in primary, secondary and higher education. He also teaches about the use of AI in education.

Workshop B

Title: Possibilities for studies with Swedish longitudinal data – an interactive workshop

UGU is one of Sweden's largest research databases in the field of education. UGU is part of the national evaluation of education, but UGU’s data is also used in social science and social research in a broad sense. 

The database contains nationally representative samples of school students from ten cohorts, born between 1948 and 2004 with the recently collected eleventh cohort of students born in 2010. The special thing about UGU is the longitudinal design where individuals from these cohorts are followed through the education system. The design makes it possible to both follow students through the education system, as well as to compare cohorts from different times. The database consists of collections from surveys and tests that are composed with school administrative data such as school, class, study choices and grades. 

The workshop consists of two parts: 

1. An informational seminar about the UGU study; and 

2. A hands-on session with UGU data to explore the research possibilities with our data.

Workshop leaders

Victoria Rolfe, Senior Lecturer, IPS, University of Gothenburg, victoria.rolfe@gu.se

Nelika Karimi, Coordinator, IPS, University of Gothenburg, nelika.karimi@gu.se

Explore the UGU website for more information on their initiatives and events. Don’t miss their upcoming conference details here.

Workshop C

Title: Register-data for educational research (SCB)

Our Swedish data registries are often described as goldmines in the context of registry-based research. The long tradition and access to unique personal identity numbers makes Sweden prominent in registry-based research. SCB’s many and extensive population-based registries are a unique and excellent resource for researchers!

Statistics Sweden (SCB) is one out of 29 agencies responsible for producing official statistics, with registries covering a variety of areas, including population and labour market statistics. In addition, we support other agencies responsible for producing official statistics through data collections and production of statistics, with one example being information on education. 

During this seminar we will present what data is available at Statistics Sweden within the education sector and how you as a researcher can be granted access to microdata.
There will also be a presentation about personal identity numbers, which is the foundation of registry-based research on individuals, about family connections via the Multi-generation Register (Flergenerationsregistret), and about some longitudinal databases that SCB provides. In addition, we will briefly discuss how to combine microdata with your own data, survey data, or data from other agencies. 

Note! This seminar will be held in Swedish, however, questions can be posed in English.

Workshop leaders

We who will be representing Statistics Sweden are Åsa Holmström and Alice Kantoniemi from the section for microdata services and our colleague from the section for education statistics Andreas Frodell.

Workshop D

Title: A Hands-On Workshop for Meta-Analyses in Educational Research

Meta-analyses are a set of statistical techniques used to combine the results of multiple studies on a specific topic. In this workshop, we will walk you through the steps for synthesising educational research findings using meta-analytic methods. Specifically, we will focus on identifying the structure of meta-analytic data sets, establishing meta-analytic baseline models, and conducting moderator analyses. You will learn about random- and mixed-effects models, heterogeneity, and multilevel meta-analysis and get to know ways of including international large-scale assessment data in the modeling phase of a meta-analysis.

The instruction and workshop material will be based on the R package “metafor” and some supplementary packages. Whether you are a researcher, statistician, or student, our workshop will provide you with the knowledge and tools to model meta-analytic data.

Workshop leaders

Ronny Scherer, is a full professor of educational assessment and measurement. He is a full professor of educational assessment and measurement. He is a member of the Centre for Educational Measurement (CEMO) and the co-director of the Centre for Research on Equality in Education (CREATE) at the University of Oslo. His research focuses on the methods and substantive issues related to research syntheses, the analysis of international large-scale assessments in education, and educational equality. ronny.scherer@cemo.uio.no

Diego Campos, is a Researcher at the Centre for Educational Measurement at the University of Oslo (CEMO). His work involves developing, evaluating, and applying methodological approaches —IPD meta-analysis and ML— to integrate large-scale data into systematic reviews and meta-analyses. Diego’s current research applies these methods to understand trends and variance in educational inequalities across education systems and over time. d.g.campos@cemo.uio.no

Here are the workshop slides and additional information for the Meta-Analysis Workshop.

This year’s QRM conference also features an invited seminar on grading and assessment. Hannes Theander and Anders Auer are inquiry secretaries at the inquiry on fair and equivalent grades and credits (U2023:02)/ Utredningen om likvärdiga betyg och meritvärden (U2023:02). The inquiry on fair and equivalent grades and credits is tasked with investigating how grades and credits can become more fair and equivalent by developing a model to link the grades to the national exams/standard tests. The lecture will be about how grades and credits can become more equal for more equal admission to the next level of education.

Anders Auer, inquiry secretary. Educational background: licentiate in economics. He has been working with educational statistics at the Swedish National Agency for Education almost 30 years with international longitudinal studies (PISA, TIMSS and PIRLS) and fair and equivalent grading.

Hannes Theander, inquiry secretary. Educational background: Pol.Mag. and teacher. He has been working with grading at the Swedish National Agency for Education for more than ten years. 

The submissions can address a large variety of educational research questions using quantitative research methods relevant to e.g., national or international large-scale assessments, as well as matters of social recruitment, segregation, and inequality throughout the educational system. We also welcome submissions that target methodological considerations and challenges. Submit your poster abstract via the poster submission form and/or your paper abstract via the paper submission form no later than April 28.

Conference venue

The address is Pedagogen Hus A, Västra Hamngatan 25, 411 17 Göteborg. 

Hotel recommendations

• Elite Plaza Hotel 
  Link to the hotel's website
• Comfort Hotel
  Link to the hotel's website